Artificial Intelligence
VSORA offers the most flexible solution on the market, by giving the user the ability to select the best combination of performance, power and cost.
Outstanding performance from IoT to ADAS and beyond!
Artificial Intelligence
The only constant in the world of AI is change. Higher processing requirements and new algorithms are introduced regularly. In this environment a solution must have high flexibility and programmability, since everything evolves rapidly, making any hard-coded approach non-viable from the start. The processing power requirements keep increasing as new AI inference and real-time processing requisites are announced. Edge AI needs low latency as well as lower energy consumption and has power constraints. Ultimately it comes down to cost = silicon area.
Highlights
Fully programmable solution
No pre-defined hardware blocks limiting efficiency. Can be re-programmed on the fly, and allows new code to be run without silicon re-spin.
High-level support
High-level framework support (TensorFlow, Caffe2, PyTorch, ONNX). Never any need to revert to low-level programming.
Scalable core
Scalable number of MACs in a singe core. User selectable between 256 and 65,536 MACs/core.
Very high memory bandwidth
Very high memory bandwidth enable loading of high number of MACs without performance impact.
No need for hardware accelerators
The flexible and highly efficient VSORA MPU cores eliminates the need for any external hardware accelerators.
Highly scalable
Solution works from IoT to ADAS and beyond.
Algorithm agnostic
Solution is algorithm agnostic - CNN, RNN, other ... If an algorithm can be expressed in Matlab, Tensorflow (or similar), C++ etc. it will run on the core(s).
Graph support
In addition to high-level language support, a user can also utilize the VSORA graph compiler to simplify programming.
Unlimited number of parallel cores
There is no limit on the number of cores that can work in parallel. From one to many!
No memory bandwidth bottleneck
No memory bandwidth bottleneck as data memory bandwidth follows processing power.
Compute precision independent of performance
Compute precision only impacts silicon area, but performance is identical regardsless of precision.
TOPs is not enough!
Efficiency and latency are other key factors to consider when planning the solution.
Below are 3 examples running ResNet50v1
All configurations using 65,536 MACs and providing 288 TOPs.
Click on the images below to find out more.